Comprehensive decision-making considerations in the transition to electrification transportation system in a developing country

To assess the technical and economic influences of the electrification transitions in the transportation system in Iran, a comparative investigation is intended to be put forward. The chief aim of this assessment is to estimate the possible benefits of the replacement of fossil fuels-based vehicles with EVs. In this way, two sections of the technical and economic analyses can be conducted. To investigate the effective aspects of electrification in Iran, a comprehensive comparison is required to measure the performance of the intended scheme. In this case, the PROMETHEE method is taken into consideration.

PROMETHEE technique

The Preference Ranking Organization METhod for Enrichment of Evaluations (PROMETHEE) is the expressive supplementary geometrical analysis for collaborative assistance. In this method, there exist preference priorities based on the designed criterion while the function with higher preference is more preferable. This method is a multi-criteria decision-making technique to rank and assess a set of substitutes based on several (in some cases contradictory) criteria. This method was established by Brans and Mareschal in the 1980s⁴⁷. The method is mainly valuable in states where a decision-maker is required to pick among numerous substitutes, respecting different quantitative and qualitative features. In this method, first, the alternatives and criteria are introduced while the criteria are effective in minimizing or maximizing the alternatives. This methodology is based on a matrix in that the alternatives and criteria are represented as rows and columns, respectively. Considering the criterion, a most favorable function that interprets the alteration in scores among couples of substitutes into an objected degree is selected. Following the procedure, a favorite index that sums the preference degrees’ overall criteria is calculated. The obtained index shows the desirable preference of that alternative over others. To conclude, considering the net rankings, strategies are ranked from the most ideal to the least favored.

It should be noted that being straightforward and simple, having high potential for flexibility, no necessity to normalize, and visual illustration are the main plus points of this technique while requiring the weights assignments, difficulty in large problems, and being highly reliant on the preferences and judgments of the decision makers are categorized as the undesirable features of this method⁴⁸. Figure 5 represents the flowchart of the PROMETHEE technique.

PROMETHEE technique flowchart.

The prioritization function pj (a, b), represented as a tool of the alteration amid two substitutes for involved standards, can be determined distinctly for all criteria to denote one alternative extent of desire to other quantitates. This formula is indicated as pj (f(a), f(b)) where its value is constantly from 0 to 1⁴⁹.

The lesser the function is, the superior the insignificance of the decision-makers would be also closer to 1, more fondness is expected. Accordingly, the function of related favorite P(a, b) of ‘a’ relating to ‘b’ can be signified as follows:

As illustrated, the most preferred function is 1 and the non-preferred function has a value equal to 0.

For the preferred functions to cover the preferential applications various shapes can be proposed e.g., linear, Gaussian, U-shape, and V-shape. Based on the form of the selected function, indifference threshold (q) and preference threshold (p) can be selected.

The index of the combined preference (\(\pi\)) for each substitute ‘a’ compared to the substitute ‘b’ can be presented as:

Here, \(\pi _j\left(a,b\right)\) signifies the collective index for multi-criteria preference for (a) over the (b), \(w_j\) represents the weight of the jth criterion, and \(p_j(a,b)\) is the preference level of (a) over (b) concerning the jth criterion. The entering currents \((\varphi ^-(a))\) and leaving currents \((\varphi ^+(a))\) of \(a_i\) are presented as:

The departure streams of an alternative (a) illustrate the inclination level for the mentioned alternative holds more appeals compared to others. The greater the departure streams become; the superior alternative will be. The incoming flows of alternatives (a) indicate the level of proficiency in comparison with other alternatives. The smaller values of departure streams are the improved alternatives. The obtained outranking streams can be computed⁴⁹:

The ultimate preference of the obtained results on the calculated net flow is more promising.

Criteria for alternative energy resources

By considering the stated background on fossil fuel resources and the intended perspective on the future of the fuel of the vehicles, various alternatives can be taken into consideration. For this determination, the confirmed substitute fuels.

In this case, various types of energy resources i.e., CNG, LPG, Gasoline (Petroleum Diesel), Hydrogen, and Electricity can be taken into account. To elaborate on these fuels, different criteria are employed to evaluate their benefits and limitations more clearly. On this pathway, technical, economic, production expenditure, distribution charge, implementation costs, infrastructure accessibility, safety, policy, social, and environmental criteria can be used as potent tools for performance evaluation. Hence, each of the influential parameters in the decision-making process to select the most suitable fuels is reviewed. The employment of various criteria can ease the difficulties of comparison evaluations. Therefore, social, economic, policy and technical criteria are considered to put forward an appropriate decision-making process. Substitutes are scored by considering 3 technical sub-criteria, 2 economical sub-criteria, 2 social sub-criteria, and 3 policy sub-criteria.

It should be stated that policy plays a significant role in the considered decision-making process. The announcement of the framework of the standardized case, risk management, conventional alignment, strategies paths, available resources, and required guidance are the main concerns in the involvement of policy as a strong factor in the decision-making process. In a structured method, this factor can contain important parameters.

Economic

Economic parameters remain one of the key influential parameters in the decision-making method by providing a strong basis to evaluate the selected system’s performance. Through these criteria, a proper comparison can be conducted between the fuels. One promising specification of the economic criterion is that this tool of measurement can be integrated into other criteria. In this case, production and distribution costs as well as implementation expenditures are involved to be assessed to provide a clear insight. Economic parameters can be effective in the short and long terms by investigating urbanization, climate change consequences, energy security, and limited oil resources⁵⁰. It is noteworthy to mention that the economy can be greatly affected by different parameters like internal rates of return, inflation rate, governmental subsidies, national taxes, etc. as may change the behavior of the projected outlook in a specific period. Moreover, the current types of ICVs have relatively lower costs than clean fuel-based vehicles or EVs. In the same vein, charges related to the production and employment of each fuel influence the overall price greatly, and afterward, the possibility of its application, as well as the degree of users’ acceptance. To elaborate on the operative factors in the economy, production, and distribution costs are elaborated. To a high extent, time developments and regional characteristics are important in the degree of production⁵¹. It has been shown that the erratic behaviors in the value of oil change the price of petroleum and substitute fuels. Conversely, costs associated with the implementation consist of the provision of a car driven by the selected fuels and related infrastructure charges⁵². Henceforth, investments and transitions to clean energies demand incentives from backbenchers and governments.

Technical

Technological advancements are a promising approach from a technical point of view. To assess the effects of the latest developments, a comparative investigation of the pros and cons of modern technologies respecting the typical and traditional facilities should be conducted. To get ahead in accomplishing the large-scale adjustment in this trend, the scientifically driven methods must be conducted by economic motivations and maintained by potent strategies. In this case, three sub-divisions can be taken to expand the area of investigation to deliver the advanced outcomes of the survey. In this case, infrastructure availability, energy content, and safety are the most important topics from a technical point of view.

The absence of appropriate infrastructure is a problem for the development of numerous novel technologies in the transportation division. To reduce the GHG releases to the environment, the infrastructure that provides these novel energy resources would be required to develop to deliver a great amount of energy to various users. An upgraded classification of the infrastructure obtainability for instance manufacturing technologies and refilling units would deliver the main influence on the upcoming efforts to commercialize the different types of energies⁵⁰. From the professional point of view, by considering the energy content, the superiorities of each introduced energy source as well as the advantages and drawbacks of the battery-powered systems can be observed⁵³.

One more point which believed to be pivotal is the fact that safety has been defined as one of the influential parameters in the technical criteria that play an unbreakable part in this area of expertise. To elaborate on this specific parameter, it should be mentioned that hazards and possible risks associated with the health and environment can be taken into consideration for further evaluation.

Social

Important concerns based on the social subjects can be addressed in this section. To be more precise, it is vital to mention the intended sub-categorizes as social acceptance and social welfare which are believed to be two potent symbols of social-related matters. One of the main downsides of the transportation systems is the GHG emissions to the environment which pulls the triggers for climate change, health problems, etc. that leads to social dissatisfaction. Initial statistics e.g., expert views, public attitudes, and insights are comprised of the planning and decision-making procedure in modern civilizations. Other points related to social acceptance can be introduced through the fees of fuel variations or imposed taxes over time which can be greatly effective⁵⁴.

Policy

GHG emissions and erratic behaviors of the oil price have provoked social discussions around the requirements of dealing with energy consumption through policy involvement. In detail, the inferior degree of consistency, which leans towards attributions of poor performance leads to the lack of reliability in policy structure or related implementations. Several aims that extend to numerous areas e.g., energy safety, environment, and fiscal progress are stated by legislators, causing the issue more probably to disturb; consequently, an upsurge in arrangement and consistency in objectives is extremely essential. Taking similar issues into consideration such as CO₂ production, energy safekeeping, and fuel trafficking, can help to upgrade the policy-related issues to the next level and link them to long- and short-term prospects^55,56.

Initial data and assumptions

To present the initial data more concisely, Table 1 provides the initial parameters to start the decision-making process. In this case, both measurable and immeasurable statistics have been considered in the assessment strategy. The entire data has been established regarding the evaluations by skilled scientists. Entire data for the alternatives are presented in Table 1. The criteria employed in this research encompass both quantitative and qualitative data. Professional experts have assessed and provided all the criteria data used in the evaluation approach. The performance values are stated by the professionals in that field by surveying.

Assortment of skilled individuals is an important assessment process of Multi-criteria analysis (MCA)/multiple-criteria decision-making (MCDM) problems. The main specification of the substitute fuels’ evaluation issue deals with various features and is taken as an MCDM, which can principally be perceived in the assortment of criteria. To provide a trustworthy assessment, reliable specialists must consensus to handle each side of the obstacles. For this determination, a reliable source of data for further study is selected⁴⁹. The value attained for each alternative can obtain a score compared to the introduced criteria which can be computed as follows:

Here, \(u_eij\) is the performance quantity based on the alternatives’ quality stated in the literature, e stands for the number of experts and referred literature, j represents the alternative to the criteria i, and N confirms the sum of advising experts or valid references. If \(u_ij>u_ik,\) the substitute j is assessed in a more efficient way than the substitute k based on criterion i, which is intended to be maximized or vice versa. Over the evaluation of this research, we have employed the obtained results from the research as cited in⁴⁹. It should be made crystal clear that in the referred research, the authors have put forward comprehensive research based on the obtained results from the officials, backbenchers, and governments. To put it simply, the investigation of this research is elaborated on their works by using their data and compiling the required data for the battery. It should be noted that the provided data for the criterion, the ref.⁴⁹ does not provide the associated data for gasoline and Li-Ion batteries. In this case, we have conducted the required investigation to find the required data by surveying the experts in these fields. In this way, we have interviewed professionals in the Meedco Company for Li-Ion battery and the National Iranian Oil Company for Li-Ion battery and gasoline data, respectively. In this way the provided ranking for the criterion details.

Each criterion’s preference function has been defined independently in light of the decision-maker’s preferences. Relating on the kind of assigned fondness function, either the fondness threshold (p), the indifferent threshold (q), or both are defined. Due to the nature of the data, a V-shaped function was constructed for the social criterion in this study and allocated to both the technical and cost-based criteria. Finally, a linear fondness function was used to process the data from the policy criterion. The p-value was set at 2 for all cost-based and technical sub-criteria excluding the energy content, while this item was regarded as 3 for the energy content sub-criteria. The p and q amount for each of the policy sub-criteria were set to 3 and 0.5, correspondingly. Table 2 presents all the criteria conditions.

The relevance of one criterion concerning another is shown by the relative weights of the criteria. Each criterion can be applied at a regulated degree of relevance based on the viewpoint of backbenchers by giving it a variable weight. In this study, five alternative scenarios were created to examine the impact of the criteria’s relative relevance on ranking from various angles.

The comparative weights of criteria specify the significance of one criterion in comparison with others. Allocating different weights to each criterion permits for controlled position regarding the decision-makers’ standpoints. In the presented work, specialists determined the criteria weights for the base case, and five additional cases were shaped to observe how changing the qualified rank of the criteria changes the rankings from dissimilar views. In the basic scenario, the contributing shares of the criteria were determined by specialists. The social criterion had the lowest amount of importance in the base scenario, with a value of 10%, and the charge criterion had a considerable status with a worth of 45%. The weighted average for the technical and policy criteria was 10% and 30%, individually. In all cases, the general weight of each criterion was spread evenly across its sub-criteria. For example, the technical criterion has a weight of 15%, which equates to 5% for each of its three sub-criteria. The weight of each criterion in each scenario is displayed in Table 3. As can be observed, by changing the influence weight of each criterion, their impacts can be assessed. In this case, the share of each criterion increased considerably to show their impacts on the final obtained outcome (scenario II-V). However, in the first scenario, the considered share is equal to each other.